High-precision indoor localization in multi-level buildings Article Swipe
Chokri Ajroud
,
Jamel Hattay
,
Mohsen Machhout
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.24425/ijet.2025.153625
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.24425/ijet.2025.153625
Accurate localization in multi-floor indoor environments is essential for applications such as large-scale inventory management, healthcare, and security systems. However, achieving high-precision tracking with passive Radio Frequency Identification (RFID) tags in these complex settings presents significant challenges, including managing vertical spatial data, reducing signal interference between floors, and maintaining computational efficiency. This paper presents a novel approach that leverages holographic algorithms to enhance the localization accuracy of passive RFID tags in multi-floor buildings. By deploying multiple RFID readers across floors and constructing 3D holographic representations from signal phase data, our approach effectively distinguishes vertical positions, allowing for precise floor-specific tracking. The proposed method achieves an average localization error of approximately 5 cm, even in multifloor environments, through optimized reader placement and computational overhead reduction. This advancement has broad applications in sectors requiring highly accurate object tracking across large, multi-level indoor spaces, positioning holographic localization as a promising solution for modern multi-floor localization needs.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.24425/ijet.2025.153625
- OA Status
- gold
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4412189627
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4412189627Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.24425/ijet.2025.153625Digital Object Identifier
- Title
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High-precision indoor localization in multi-level buildingsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-11Full publication date if available
- Authors
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Chokri Ajroud, Jamel Hattay, Mohsen MachhoutList of authors in order
- Landing page
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https://doi.org/10.24425/ijet.2025.153625Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.24425/ijet.2025.153625Direct OA link when available
- Concepts
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Computer science, Remote sensing, Environmental science, Architectural engineering, Artificial intelligence, Geography, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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